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Â Okay, so in this last video,

Â we're going to have a look at two additional tools which you may use.

Â To find the best performing managers, adjusted to some kind of risk measure.

Â And actually, this is one of my preferred measures, and

Â I'll explain to you why I quite like this measurement.

Â This risk-adjusted performance ratio, which is not as common as sharp or

Â [UNKNOWN, but in my view has something very right to it.

Â So what we'll do, we'll talk about the MAR ratio, and

Â MAR comes from a newsletter which has been around for many, many years.

Â And it actually says Manager Report Newsletter, and

Â it has an emphasis on hedge fund analysis or

Â indeed exactly what we're discussing here, peer group analysis.

Â 1:28

And the drawdown to me is why I like this ratio,

Â it's actually a notion of risk which makes probably

Â more sense than is intuitively to a customer.

Â Who hasn't gone maybe to university and does not really know

Â what a standard deviation is, and may have difficulty in grasping it.

Â Especially, so if that standard deviation captures

Â a return which exceeds the average.

Â This may be somewhat difficult for somebody to associate that to risk.

Â But certainly, a notion that is more straightforward

Â to be identified with risk is the notion of maximum loss or

Â maximum drawdown or also [INAUDIBLE].

Â Basically, you say the worst you could lose by buying this security or

Â this investment fund is so much and this to me has a very clear meaning okay.

Â So a MAR ratio in excess of 2 will be

Â a manager who delivers maybe 92% total

Â return since inception as we see here and

Â has had a maximum loss of 46%.

Â So 96 divided by 46 is 2.

Â And just to highlight again, you've seen this chart already, but

Â what the drawdown means.

Â It's the worst possible scenario of entering the market

Â at the peak here in 2000 and exiting the market when fear is at its maximum.

Â In 2002, and there you lose 46% and this will be your drawdown, okay.

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So, using the MAR ratio to identify especially when you have no

Â benchmark in terms of markets, market indices may prove a very.

Â A useful measure and indeed, also something which is simple to grasp.

Â You compare the total return since inception, and

Â you divide it by the maximum loss.

Â Simple and intuitively appealing but now there's a shortcoming to this MAR ratio.

Â And I want to illustrate that with the following examples.

Â Assume we have two managers.

Â Manager A has a CAGR, that's compounded annual growth rate,

Â total of 40%, so since inception and

Â a Drawdown, a maximum loss of 20, so a MAR ratio of 2.

Â Manger B has slightly above total return of 50% but

Â also are sharper Drawdown 30%,

Â so 50 divided by 30 is 1.66.

Â Okay, so the first manager, Manager A has a higher MAR ratio,

Â so you would be tempted to your being climbed to allocate all

Â your investment to him and not to Manager B.

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But what if I now tell you that Manager B has been around for

Â 20 years and Manager A only for 5 years?

Â S clearly, you would say Manager B has more experience and may be, he has

Â a greater Drawdown because that Drawdown happened when Manager A did not exist.

Â If Manager A had existed then, may be he would have experienced a greater loss.

Â So, the way to solve the shortcoming of the MAR ratio is the CALMAR ratio.

Â And the CALMAR ratio is quite simply the same ratio of the MAR ratio but here,

Â instead of looking at the worst possible loss over its inception.

Â Basically, here, you're looking at the worst loss over the last 36 months or

Â the last 3 years.

Â So, CALMAR and MAR ratio need to be used together

Â because maybe the idea of a maximum loss of 5% within the last 3 years.

Â Does not give you an accurate picture because maybe the fund is

Â actually far more riskier than that and has experience of 46% loss 15 years ago.

Â So you need to use both but at least you can be sure that using

Â the CALMAR ratio you're comparing apples with apples.

Â And you're comparing managers who have been in existence and

Â over the same time period.

Â And clearly, this is something that is obviously very important to mention.

Â When you are doing this filtering, when you are extracting

Â from the database, managers based on return statistics,

Â risk measurements percentages of positive months and etc., etc.

Â You need to make sure that you are comparing apples with apples and

Â that all the managers have a similar mandate when investing their funds.

Â So in conclusion of this set of two videos,

Â we've seen here that to perform the peer group analysis.

Â What you need is a good database that will have

Â managers which are ranked by categories.

Â And we need to make sure that this is done professionally and each category,

Â you do find managers that have a specific investment philosophy.

Â And then, basically, you can filter that data base using

Â criteria's which best suit your investment philosophy.

Â I give you one example.

Â If you want to assemble a fund of funds which will be low risk,

Â then you will put a lot of emphasis on extracting from your database.

Â Managers who have the highest proportion of positive months

Â who have the minimum draw down, who have the lowest volatility.

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All these kind of risk measurements which you will be put an emphasis upon.

Â So, on the other hand, if you're looking for the really strong growth,

Â then you may be just shooting for the maximum vita.

Â The people who use leverage and maximum return strategy,

Â you have put more emphasis on return, so this all depends on your philosophy.

Â And then, in the second video, we saw a measurement,

Â which in my view, is very useful when we are talking about peer group analysis.

Â And we don't have a benchmark to compare

Â ourselves too, so basically here we are just looking at a total return

Â dividing that total return by the maximum loss.

Â And this is to me a very intuitively appealing notion of risk.

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Â